Plants Disease Identification and Classification Through Leaf Images: A Survey

The symptoms of plant diseases are evident in different parts of a plant; however leaves are found to be the most commonly observed part for detecting an infection. Researchers have thus attempted to automate the process of plant disease detection and classification using leaf images. Several works utilized computer vision technologies effectively and contributed a lot in this domain. This manuscript summarizes the pros and cons of all such studies to throw light on various important research aspects. A discussion on commonly studied infections and research scenario in different phases of a disease detection system is presented. The performance of state-of-the-art techniques are analyzed to identify those that seem to work well across several crops or crop categories. Discovering a set of acceptable techniques, the manuscript highlights several points of consideration along with the future research directions. The survey would help researchers to gain understanding of computer vision applications in plant disease detection.

[1]  S. Zhang,et al.  Plant disease recognition based on plant leaf image. , 2015 .

[2]  Yeni Herdiyeni,et al.  Paddy diseases identification with texture analysis using fractal descriptors based on fourier spectrum , 2013, 2013 International Conference on Computer, Control, Informatics and Its Applications (IC3INA).

[3]  Yogesh H. Dandawate,et al.  An automated approach for classification of plant diseases towards development of futuristic Decision Support System in Indian perspective , 2015, 2015 International Conference on Advances in Computing, Communications and Informatics (ICACCI).

[4]  Qing Guo,et al.  Improved rotation kernel transformation directional feature for recognition of wheat stripe rust and powdery mildew , 2014, 2014 7th International Congress on Image and Signal Processing.

[5]  Daniel Cremers,et al.  An image classification approach to analyze the suppression of plant immunity by the human pathogen Salmonella Typhimurium , 2012, BMC Bioinformatics.

[6]  Asit Kumar Das,et al.  Rice diseases classification using feature selection and rule generation techniques , 2013 .

[7]  S. K. Satpathy,et al.  A Step towards Precision Farming of Rice Crop by Estimating Loss Caused by Leaf Blast Disease Using Digital Image Processing and Fuzzy Clustering , 2011 .

[8]  Vijay S. Rajpurohit,et al.  “Diagnosis and classification of grape leaf diseases using neural networks” , 2013, 2013 Fourth International Conference on Computing, Communications and Networking Technologies (ICCCNT).

[9]  Hiteshwari Sabrol,et al.  Fuzzy and Neural Network based Tomato Plant Disease Classification using Natural Outdoor Images , 2016 .

[10]  S. Phadikar,et al.  Classification of Rice Leaf Diseases Based onMorphological Changes , 2012 .

[11]  Shanu Sharma,et al.  Leaf disease detection and grading using computer vision technology & fuzzy logic , 2015, 2015 2nd International Conference on Signal Processing and Integrated Networks (SPIN).

[12]  Jagadeesh Pujari,et al.  Image Processing Based Detection of Fungal Diseases in Plants , 2015 .

[13]  Luciano Vieira Koenigkan,et al.  Identifying multiple plant diseases using digital image processing , 2016 .

[14]  D. S. Hooda,et al.  Statistical Texture and Normalized Discrete Cosine Transform-Based Automatic Soya Plant Foliar Infection Cataloguing , 2014 .

[15]  Jeremy S. Smith,et al.  An image-processing based algorithm to automatically identify plant disease visual symptoms. , 2009 .

[16]  D. S. Hooda,et al.  Automatic Brown Spot and Frog Eye Detection from the Image Captured in the Field , 2014 .

[17]  Norman C. Elliott,et al.  Using digital image analysis and spectral reflectance data to quantify damage by greenbug (Hemitera: Aphididae) in winter wheat , 2006 .

[18]  S. Palanivel,et al.  Detection and Recognition of Diseases from Paddy Plant Leaf Images , 2016 .

[19]  Chunbo Xiu,et al.  A Curvelet-SC Recognition Method for Maize Disease , 2015, J. Electr. Comput. Eng..

[20]  Jian Tang,et al.  Application of Support Vector Machine for Detecting Rice Diseases Using Shape and Color Texture Features , 2009, 2009 International Conference on Engineering Computation.

[21]  Aprinaldi,et al.  Detection of Palm Oil Leaf Disease with Image Processing and Neural Network Classification on Mobile Device , 2013 .

[22]  S. Arivazhagan,et al.  Detection of unhealthy region of plant leaves and classification of plant leaf diseases using texture features , 2013 .

[23]  Jayme Garcia Arnal Barbedo,et al.  Digital image processing techniques for detecting, quantifying and classifying plant diseases. , 2013 .

[24]  Dipak Kumar Kole,et al.  Detection of Downy Mildew Disease Present in the Grape Leaves Based on Fuzzy Set Theory , 2014 .

[25]  Min Zhang,et al.  Automatic citrus canker detection from leaf images captured in field , 2011, Pattern Recognit. Lett..

[26]  Ujjwal Bhattacharya,et al.  Color Texture Analysis of Rice Leaves Diagnosing Deficiency in the Balance of Mineral Levels towards Improvement of Crop Productivity , 2007 .

[27]  Jayme Garcia Arnal Barbedo,et al.  A review on the main challenges in automatic plant disease identification based on visible range images , 2016 .

[28]  S. Gharge,et al.  Image Processing for Soybean Disease Classification and Severity Estimation , 2016 .

[29]  Nooritawati Md Tahir,et al.  Overview of image processing approach for nutrient deficiencies detection in Elaeis Guineensis , 2011, ICSET 2011.

[30]  Satish Kumar Singh,et al.  Color sensing and image processing-based automatic soybean plant foliar disease severity detection and estimation , 2015, Multimedia Tools and Applications.

[31]  S. Dhaygude.  Crop Disease Detection Using CBIR , 2013 .

[32]  Sudheer Reddy Bandi,et al.  PERFORMANCE EVALUATION OF VARIOUS STATISTICAL CLASSIFIERS IN DETECTING THE DISEASED CITRUS LEAVES , 2013 .

[33]  Atul Shire,et al.  A Review Paper On: Agricultural Plant Leaf Disease Detection Using Image Processing , 2015 .

[34]  Ujwalla Gawande,et al.  An Overview of the Research on Plant Leaves Disease detection using Image Processing Techniques , 2014 .

[35]  Jayamala K. Patil,et al.  Advances in Image Processing for Detection of Plant Disease , 2017 .

[36]  Salwani Abdullah,et al.  Investigation on Image Processing Techniques for Diagnosing Paddy Diseases , 2009, 2009 International Conference of Soft Computing and Pattern Recognition.

[37]  Shen Weizheng,et al.  Grading Method of Leaf Spot Disease Based on Image Processing , 2008, 2008 International Conference on Computer Science and Software Engineering.

[38]  Massimo Marchi,et al.  Automatic detection of powdery mildew on grapevine leaves by image analysis: Optimal view-angle range to increase the sensitivity , 2014 .

[39]  Kuo-Yi Huang.  Application of artificial neural network for detecting Phalaenopsis seedling diseases using color and texture features , 2007 .

[40]  Tae-Soo Chon,et al.  Plant leaf detection using modified active shape models , 2013 .

[41]  M. Ramakrishnan,et al.  Groundnut leaf disease detection and classification by using back probagation algorithm , 2015, 2015 International Conference on Communications and Signal Processing (ICCSP).

[42]  Murali Krishnan,et al.  A novel algorithm for detecting bacterial leaf scorch (BLS) of shade trees using image processing , 2013, 2013 IEEE 11th Malaysia International Conference on Communications (MICC).

[43]  J. Pujari,et al.  Quantitative detection of soybean rust using image processing techniques , 2015 .

[44]  R. V. Kshirsagar,et al.  Cotton leaf disease identification using pattern recognition techniques , 2015, 2015 International Conference on Pervasive Computing (ICPC).

[45]  Minzan Li,et al.  Detection of soybean rust using a multispectral image sensor , 2009 .

[46]  A. B. Patil,et al.  Plant Disease Detection Using Image Processing , 2015, 2015 International Conference on Computing Communication Control and Automation.

[47]  Shanwen Zhang,et al.  Orthogonal Locally Discriminant Projection for Classification of Plant Leaf Diseases , 2013, 2013 Ninth International Conference on Computational Intelligence and Security.

[48]  Di Cui,et al.  Image processing methods for quantitatively detecting soybean rust from multispectral images , 2010 .

[49]  Tian Youwen,et al.  The Recognition of Cucumber Disease Based on Image Processing and Support Vector Machine , 2008, 2008 Congress on Image and Signal Processing.

[50]  S. Pethybridge,et al.  Leaf Doctor: A New Portable Application for Quantifying Plant Disease Severity. , 2015, Plant disease.

[51]  Yan Yue,et al.  The Identification of Powdery Mildew Spores Image Based on the Integration of Intelligent Spore Image Sequence Capture Device , 2013, 2013 Ninth International Conference on Intelligent Information Hiding and Multimedia Signal Processing.

[52]  Wang Xianfeng,et al.  PNN based crop disease recognition with leaf image features and meteorological data , 2015 .

[53]  Hugo Franco,et al.  Automatic detection of early blight infection on tomato crops using a color based classification strategy , 2014, 2014 XIX Symposium on Image, Signal Processing and Artificial Vision.

[54]  Wolfgang Förstner,et al.  The potential of automatic methods of classification to identify leaf diseases from multispectral images , 2011, Precision Agriculture.

[55]  Sumeet S. Nisale,et al.  Detection and Analysis of Deficiencies in Groundnut Plant using Geometric Moments , 2011 .

[56]  Yongqiang Ye,et al.  Use of leaf color images to identify nitrogen and potassium deficient tomatoes , 2011, Pattern Recognit. Lett..

[57]  Malik Braik,et al.  A framework for detection and classification of plant leaf and stem diseases , 2010, 2010 International Conference on Signal and Image Processing.

[58]  Reza Ehsani,et al.  Review: A review of advanced techniques for detecting plant diseases , 2010 .

[59]  Jagadeesh Pujari,et al.  SVM and ANN Based Classification of Plant Diseases Using Feature Reduction Technique , 2016, Int. J. Interact. Multim. Artif. Intell..

[60]  Clive H. Bock,et al.  Plant Disease Severity Estimated Visually, by Digital Photography and Image Analysis, and by Hyperspectral Imaging , 2010 .

[61]  Su Hang,et al.  A Research of Maize Disease Image Recognition of Corn Based on BP Networks , 2011, 2011 Third International Conference on Measuring Technology and Mechatronics Automation.

[62]  J. Massah,et al.  An artificial neural network approach to identify fungal diseases of cucumber (Cucumis sativus L.) plants using digital image processing , 2013 .

[63]  J. Sil,et al.  Rice disease identification using pattern recognition techniques , 2008, 2008 11th International Conference on Computer and Information Technology.

[64]  Aruna Chakraborty,et al.  An Integrated Digital Image Analysis System for Detection, Recognition and Diagnosis of Disease in Wheat Leaves , 2015, WCI '15.

[65]  A. Ferrer,et al.  Pixel classification methods for identifying and quantifying leaf surface injury from digital images , 2014 .

[66]  Cristina E. Davis,et al.  Advanced methods of plant disease detection. A review , 2014, Agronomy for Sustainable Development.

[67]  Xiaolong Li,et al.  Application of neural networks to image recognition of plant diseases , 2012, 2012 International Conference on Systems and Informatics (ICSAI2012).

[68]  José F. Rodrigues,et al.  Local descriptors for soybean disease recognition , 2016, Comput. Electron. Agric..

[69]  W. S. Lee,et al.  Identification of citrus disease using color texture features and discriminant analysis , 2006 .

[70]  Kendra Schwartz,et al.  Characterizing inflammatory breast cancer among Arab Americans in the California, Detroit and New Jersey Surveillance, Epidemiology and End Results (SEER) registries (1988–2008) , 2012, SpringerPlus.

[71]  Jayme Garcia Arnal Barbedo,et al.  An Automatic Method to Detect and Measure Leaf Disease Symptoms Using Digital Image Processing. , 2014, Plant disease.

[72]  A. K. Misra,et al.  Detection of unhealthy region of plant leaves using image processing and genetic algorithm , 2015, 2015 International Conference on Advances in Computer Engineering and Applications.

[73]  Jeremy S. Smith,et al.  Image pattern classification for the identification of disease causing agents in plants , 2009 .

[74]  Hao Li,et al.  A New Method for Soybean Leaf Disease Detection Based on Modified Salient Regions , 2015, MUE 2015.

[75]  Marcel Salathé,et al.  Using Deep Learning for Image-Based Plant Disease Detection , 2016, Front. Plant Sci..

[76]  Aruna Chakraborty,et al.  Application of Fuzzy C-Means Clustering Method to Classify Wheat Leaf Images Based on the Presence of Rust Disease , 2014, FICTA.

[77]  Sanjay B. Patil,et al.  Grading of Soybean Leaf Disease Based on Segmented Image Using K-means Clustering , 2016 .

[78]  Jesús Carlos Pedraza Ortega,et al.  KNN-based image segmentation for grapevine potassium deficiency diagnosis , 2016, CONIELECOMP.

[79]  A. Srikaew,et al.  Grape leaf disease detection from color imagery using hybrid intelligent system , 2008, 2008 5th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology.

[80]  Rajneesh Talwar,et al.  A Review on Efficient Identification of American Cotton Leaf Diseases through Training Set , 2015 .

[81]  L. Plümer,et al.  Original paper: Early detection and classification of plant diseases with Support Vector Machines based on hyperspectral reflectance , 2010 .

[82]  N. Wickramarachchi,et al.  An image recognition system for crop disease identification of paddy fields in Sri Lanka , 2009, 2009 International Conference on Industrial and Information Systems (ICIIS).

[83]  Darko Stefanovic,et al.  Deep Neural Networks Based Recognition of Plant Diseases by Leaf Image Classification , 2016, Comput. Intell. Neurosci..

[84]  Mahdi Kadivar,et al.  Effect of dietary flaxseed oil level on the growth performance and fatty acid composition of fingerlings of rainbow trout, Oncorhynchus mykiss , 2013, SpringerPlus.

[85]  P. Lammers,et al.  Smart detection of leaf wilting by 3D image processing and 2D Fourier transform , 2013 .

[86]  Debashis Ghosh,et al.  Multi-resolution mobile vision system for plant leaf disease diagnosis , 2016, Signal Image Video Process..

[87]  Marian Wiwart,et al.  Early diagnostics of macronutrient deficiencies in three legume species by color image analysis , 2009 .

[88]  Z. B. Husin,et al.  Feasibility Study on Plant Chili Disease Detection Using Image Processing Techniques , 2012, 2012 Third International Conference on Intelligent Systems Modelling and Simulation.

[89]  Rabia Masood,et al.  Plants Disease Segmentation using Image Processing , 2016 .

[90]  Sabeen Survery,et al.  Increased Permeability of the Aquaporin SoPIP2;1 by Mercury and Mutations in Loop A , 2016, Front. Plant Sci..